An Analysis on Danish Micro Data - School of Economics and ...
An Analysis on Danish Micro Data - School of Economics and ...
An Analysis on Danish Micro Data - School of Economics and ...
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use<strong>of</strong>m~n | -.000043 .00003 -1.26 0.208 -.00011 .000024 866.898<br />
u | -.0321611 .02077 -1.55 0.122 -.072872 .008549 6.07914<br />
------------------------------------------------------------------------------<br />
(*) dy/dx is for discrete change <strong>of</strong> dummy variable from 0 to 1<br />
Pooled probit – Tables 3 & 5:<br />
. use /akf/702517/ycb2517/Initial/finaldata2.dta<br />
.<br />
. /*Same estimati<strong>on</strong> as Galarraga, with some extra variables though - robust std<br />
> errors - with proxy Generalised residual*/<br />
. quietly probit ad_dummy mtx wageinc age ab02 ab36 ab79 ab1014 single iel<strong>and</strong>1<br />
> iel<strong>and</strong>2 short higher agesq use<strong>of</strong>medicin u y96 y97 y98 y99 y00 y01 y02 y03, ro<br />
> bust<br />
.<br />
. predict xb, xb<br />
. gen normxb=norm(xb)<br />
. gen normdenxb=normden(xb)<br />
. gen denominator=normxb*[1-normxb]<br />
. gen numerator=normdenxb*[ad_dummy-normxb]<br />
. gen res=numerator/denominator<br />
.<br />
. probit emp ad_dummy mtx wageinc age ab02 ab36 ab79 ab1014 single iel<strong>and</strong>1 iela<br />
> nd2 short higher agesq use<strong>of</strong>medicin u res y96 y97 y98 y99 y00 y01 y02 y03, ro<br />
> bust<br />
Iterati<strong>on</strong> 0: log pseudolikelihood = -2397.2264<br />
Iterati<strong>on</strong> 1: log pseudolikelihood = -1167.9958<br />
Iterati<strong>on</strong> 2: log pseudolikelihood = -904.42415<br />
Iterati<strong>on</strong> 3: log pseudolikelihood = -846.90787<br />
Iterati<strong>on</strong> 4: log pseudolikelihood = -839.68757<br />
Iterati<strong>on</strong> 5: log pseudolikelihood = -839.52979<br />
Iterati<strong>on</strong> 6: log pseudolikelihood = -839.5297<br />
Probit estimates Number <strong>of</strong> obs = 3508<br />
Wald chi2(25) = 748.75<br />
Prob > chi2 = 0.0000<br />
Log pseudolikelihood = -839.5297 Pseudo R2 = 0.6498<br />
------------------------------------------------------------------------------<br />
| Robust<br />
emp | Coef. Std. Err. z P>|z| [95% C<strong>on</strong>f. Interval]<br />
-------------+----------------------------------------------------------------<br />
ad_dummy | .7296951 1.652585 0.44 0.659 -2.509313 3.968703<br />
mtx | .0002294 .0003915 0.59 0.558 -.0005379 .0009967<br />
wageinc | .000017 8.21e-07 20.70 0.000 .0000154 .0000186<br />
age | -.0038895 .0189568 -0.21 0.837 -.0410441 .0332651<br />
ab02 | -.1581035 .216709 -0.73 0.466 -.5828453 .2666382<br />
ab36 | -.3409842 .1580029 -2.16 0.031 -.6506643 -.0313042<br />
ab79 | -.0622015 .1326735 -0.47 0.639 -.3222369 .1978339<br />
ab1014 | -.2602254 .107907 -2.41 0.016 -.4717192 -.0487315<br />
97
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